This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,cons...This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.展开更多
To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance dat...To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to es...This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs.Secondly,the unknown parameter linearly associated with control input is acquired by the adaptive control approach,and a discrete time extended state observer is designed to estimate nonlinear uncertainties.Thirdly,in order to achieve the prescribed performance,the constrained bipartite consensus error is transformed through a strictly increasing function.Based on the converted equivalent unconstrained error function,a sliding mode controller using only the input and output data of the MASs is designed.Finally,the efficacy of the controller is confirmed by simulations.展开更多
Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with ...Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with the pulse response iterative correction(PRIC).The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error.The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way.It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio.A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control(GOILC)with its approximated one updated in the correction algorithm.The convergences regarding tracking error and correction error are obtained monotonically.Finally,numerical simulation verifies the validity and effectiveness.展开更多
In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a lar...In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.展开更多
Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynam...Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynamics control.For this purpose,this paper studies the DYC through the Takagi-Sugeno(T-S)fuzzy-based model predictive control to deal with the nonlinear challenge.First,a T-S fuzzy-based vehicle dynamics model is established to describe the time-varying tire cornering stiffness and vehicle speeds,and thus the uncertain parameters can be represented by the norm-bounded uncertainties.Then,a robust model predictive control(MPC)is developed to guarantee vehicle handling stability.A feasible solution can be obtained through a set of linear matrix inequalities(LMIs).Finally,the tests are conducted by the Carsim/Simulink joint platform to verify the proposed method.The comparative results show that the proposed strategy can effectively guarantee the vehicle’s lateral stability while handling the nonlinear challenge.展开更多
Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands...Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.展开更多
The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in ou...The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in outdoor settings.In this study,we developed cyborg locusts capable of performing directional locomotion in intricate outdoor environments,including jumping over obstacles,climbing slopes,traversing narrow pipelines,and accurately reaching predetermined targets along specified routes.We designed a miniature electrical backpack(10 mm×10 mm,0.75 g)capable of receiving stimulus parameters(frequency,duty ratio,and stimulation time)via Bluetooth commands from mobile phones.Electrical stimulation of locust sensory organs,such as the antennae and cercus,induced turning and jumping behaviors.Experi-mental testing of locust movement control was conducted under outdoor conditions with a short electrical stimulation interval.Results showed a positive correlation between locust turning angles and electrical stimulation parameters within a specified range,with an average jumping height exceeding 10 cm.Additionally,the success rate of locust turning and jumping behaviors correlated positively with the interval time between electrical stimulations.Adjusting these intervals during forward crawling phases increased the likelihood of the locusts jumping again.In conclusion,this study success-fully achieved directional locomotion control of cyborg locusts outdoors,providing insights and references for advancing search and rescue capabilities.展开更多
The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.H...The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.However,further exploration is required to suppress the outward thermal losses from the nanofluid at high temperatures.Herein,this paper proposes a novel NDASC in which the outer surface of the collector tube is covered with functional coatings and a three-dimensional computational fluid dynamics model is established to study the energy flow distributions on the collector within the temperature range of 400-600 K.When the nanofluid’s absorption coefficient reaches 80 m^(-1),the NDASC shows the optimal thermal performance,and the NDASC with local Sn-In_(2)O_(3) coating achieves a 7.8% improvement in thermal efficiency at 400 K compared to the original NDASC.Furthermore,hybrid coatings with Sn In_(2)O_(3)/WTi-Al_(2)O_(3) are explored,and the optimal coverage angles are determined.The NDASC with such coatings shows a 10.22%-17.9% increase in thermal efficiency compared to the original NDASC and a 7.6%-19.5% increase compared to the traditional surface-type solar collectors,demonstrating the effectiveness of the proposed energy flow control strategy for DASCs.展开更多
Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic c...Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.展开更多
Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net ...Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net shapes.This technology is gathering increasing attention from industries such as biomedical,automotive,and aerospace.However,achieving consistent part quality and desired material properties is challenging due to intricate processing parameters and potential process defects such as dynamic melt-pool behavior and localized heat accumulation.This paper reviews recent advances in on-line quality control,focusing on in-situ measurement and closed-loop control for efficient assurance of LDED-fabricated parts.The quality principles,encompassing accuracy and material performance,are summarized to lay a foundation for understanding the mechanisms of quality defects and influencing factors.This review explores and thoroughly compares advancements in indirect process measurements,such as optical,thermal,and acoustic monitoring with direct quality measurements,including laser-line scanning and operando synchrotron X-ray imaging.Depending on the sensing techniques,this paper highlights a hierarchical control strategy for adaptive parameter regulation on intra-layer and inter-layer scales.The requirements and performance of various state-of-the-art controllers are critically compared to indicate their suitable applications.The importance of machine learning in detecting process anomalies and predicting build quality based on sensory signals is also outlined.Future directions are proposed towards adaptive,automated,and intelligent quality control,with a focus on multi-modal monitoring,physics-informed neural networks for interpretable analysis,and multi-objective control applications.展开更多
The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many ba...The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.展开更多
For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And dir...For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And direct yaw-moment control(DYC)has been widely studied and applied to vehicle stability control.Good vehicle handling performance:quick yaw rate transient response,small overshoot,high steady yaw rate gain,etc,is required by drivers under normal conditions,which is less concerned,however.Based on the hierarchical control methodology,a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed.The upper-loop control system consists of two parts:a state feedback controller,which aims to realize the ideal transient response of yaw rate,with a vehicle sideslip angle observer;and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain.Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors,the integrated time and absolute error(ITAE)function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix.Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method:yaw rate rising time is reduced,steady yaw rate gain is increased,vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced.The control system improves vehicle handling performance under normal conditions in both transient and steady response.State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.展开更多
Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilize...Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilizers) with the conventional urea. Six treatments including CK (no N fertilizer), conventional urea and different types of LP fertilizers at different rates were designed for two succeeding crops of early and late rice. A blend of different types of LP fertilizers as a single preplant "co-situs" application released N in a rate and amount synchronizing with uptake pattern of direct seeding rice. A single preplant application of the LP fertilizers could meet the N requirement of rice for the whole growth period without need of topdressing. Using LP fertilizer blends, equivalent grain yields could be maintained even if the N fertilization rates were reduced by 25%～50% compared with the conventional urea. Agronomic efficiency of the LP fertilizers was 13.6%～ 86.4% higher than that of the conventional urea in early rice and 100%～164.1% in late rice, depending on the amounts of the LP fertilizers applied. N fertilizer recovery rate increased from 27.4% for the conventional application of urea to 41.7%～54.l% for the single preplant "co-situs" application of the LP fertilizers. Use of the LP fertilizers was promising if the increase in production costs due to the high LP fertilizer prices could be compensated by increase in yield and N efficiency, reduction in labor costs and improvement in environment.展开更多
This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a...This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.展开更多
Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable...Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.展开更多
Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training a...Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.展开更多
基金Natural Science Basic Research Plan in Shaanxi Province of China(2023-JC-QN-0733).
文摘This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.
基金supported in part by the National Natural Science Foundation of China,Grant/Award Number:62003267the Key Research and Development Program of Shaanxi Province,Grant/Award Number:2023-GHZD-33Open Project of the State Key Laboratory of Intelligent Game,Grant/Award Number:ZBKF-23-05。
文摘To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金supported in part by the National Natural Science Foundation of China(62373113,62433014,62433018)the Guangdong Basic and Applied Basic Research Foundation(2023A1515011527,2023B1515120010).Recommended by Associate Editor Xiaohua Ge。
文摘This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems(MASs)based on data-driven adaptive method.To begin with,a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs.Secondly,the unknown parameter linearly associated with control input is acquired by the adaptive control approach,and a discrete time extended state observer is designed to estimate nonlinear uncertainties.Thirdly,in order to achieve the prescribed performance,the constrained bipartite consensus error is transformed through a strictly increasing function.Based on the converted equivalent unconstrained error function,a sliding mode controller using only the input and output data of the MASs is designed.Finally,the efficacy of the controller is confirmed by simulations.
基金supported by the National Natural Science Foundation of China(619733380).
文摘Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable,the paper explores a data-driven adaptive iterative learning control(DDAILC)strategy that interacts with the pulse response iterative correction(PRIC).The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error.The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way.It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio.A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control(GOILC)with its approximated one updated in the correction algorithm.The convergences regarding tracking error and correction error are obtained monotonically.Finally,numerical simulation verifies the validity and effectiveness.
基金supported in part by the National Natural Science Foundation of China(62473142,62203161)Special Funding Support for the Construction of Innovative Provinces in Hunan Province(2021GK1010)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2024A1515011579),Project of State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle(72275007).
文摘In this paper,a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems(MRSs)under a directed communication topology.The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction.By the signed graph theory,it is further transformed into a bipartite consensus control problem,where all followers are uniformly degenerated into the general nonlinear systems based on the lateral error model.To augment the flexibility of control protocol and improve control performance,a higher-dimensional full form dynamic linearization(FFDL)technique is committed to the MRSs.The control input criterion function consists of the data model based on FFDL and the bipartite consensus error based on the signed graph theory,and the proposed control protocol is given by optimizing this criterion function.In this way,this scheme has a higher degree of freedom and better adaptive adjustment capability while not excessively increasing the control method complexity,and it can also be compatible with other forms of dynamic linearization techniques in MRSs.Further,three matrix norm lemmas are introduced to deal with the challenges of stability analysis caused by higher matrix dimensions and more robots.Finally,the effectiveness of the proposed method is verified by numerical simulations.
基金Supported by National Natural Science Foundation of China(Grant Nos.52402497,52025121 and 52002066)Young Scientists Project and General Project of Applied Basic Research in Yunnan Province(Grant Nos.202501AT070296,202401AU070196)+1 种基金The Key Laboratory of Modern Agricultural Engineering of Ordinary Colleges and Universities of Education Department of Autonomous Region(Grant No.TDNG2023108)Jiangsu Provincial Achievements Transformation Project(Grant No.BA2018023).
文摘Distributed drive electric vehicles(DDEVs)endow the ability to improve vehicle stability performance through direct yaw-moment control(DYC).However,the nonlinear characteristics pose a great challenge to vehicle dynamics control.For this purpose,this paper studies the DYC through the Takagi-Sugeno(T-S)fuzzy-based model predictive control to deal with the nonlinear challenge.First,a T-S fuzzy-based vehicle dynamics model is established to describe the time-varying tire cornering stiffness and vehicle speeds,and thus the uncertain parameters can be represented by the norm-bounded uncertainties.Then,a robust model predictive control(MPC)is developed to guarantee vehicle handling stability.A feasible solution can be obtained through a set of linear matrix inequalities(LMIs).Finally,the tests are conducted by the Carsim/Simulink joint platform to verify the proposed method.The comparative results show that the proposed strategy can effectively guarantee the vehicle’s lateral stability while handling the nonlinear challenge.
文摘Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX22_0290.
文摘The ability of cyborg locusts to achieve directional movement in complex outdoor environments is critical for search and rescue missions.Currently,there is a lack of research on motion control for cyborg locusts in outdoor settings.In this study,we developed cyborg locusts capable of performing directional locomotion in intricate outdoor environments,including jumping over obstacles,climbing slopes,traversing narrow pipelines,and accurately reaching predetermined targets along specified routes.We designed a miniature electrical backpack(10 mm×10 mm,0.75 g)capable of receiving stimulus parameters(frequency,duty ratio,and stimulation time)via Bluetooth commands from mobile phones.Electrical stimulation of locust sensory organs,such as the antennae and cercus,induced turning and jumping behaviors.Experi-mental testing of locust movement control was conducted under outdoor conditions with a short electrical stimulation interval.Results showed a positive correlation between locust turning angles and electrical stimulation parameters within a specified range,with an average jumping height exceeding 10 cm.Additionally,the success rate of locust turning and jumping behaviors correlated positively with the interval time between electrical stimulations.Adjusting these intervals during forward crawling phases increased the likelihood of the locusts jumping again.In conclusion,this study success-fully achieved directional locomotion control of cyborg locusts outdoors,providing insights and references for advancing search and rescue capabilities.
基金Project(52476095)supported by the National Natural Science Foundation of ChinaProject(kq2506013)supported by Changsha Outstanding Innovative Youth Training Program,China。
文摘The nanofluid-based direct absorption solar collector(NDASC)ensures that solar radiation passing through the tube wall is directly absorbed by the nanofluid,reducing thermal resistance in the energy transfer process.However,further exploration is required to suppress the outward thermal losses from the nanofluid at high temperatures.Herein,this paper proposes a novel NDASC in which the outer surface of the collector tube is covered with functional coatings and a three-dimensional computational fluid dynamics model is established to study the energy flow distributions on the collector within the temperature range of 400-600 K.When the nanofluid’s absorption coefficient reaches 80 m^(-1),the NDASC shows the optimal thermal performance,and the NDASC with local Sn-In_(2)O_(3) coating achieves a 7.8% improvement in thermal efficiency at 400 K compared to the original NDASC.Furthermore,hybrid coatings with Sn In_(2)O_(3)/WTi-Al_(2)O_(3) are explored,and the optimal coverage angles are determined.The NDASC with such coatings shows a 10.22%-17.9% increase in thermal efficiency compared to the original NDASC and a 7.6%-19.5% increase compared to the traditional surface-type solar collectors,demonstrating the effectiveness of the proposed energy flow control strategy for DASCs.
基金supported by the National Natural Science Foundation of China(No.52372371)the Science Center for Gas Turbine Project,China(Nos.P2022-B-V-002-001,P2022-B-V-001-001).
文摘Direct Thrust Control(DTC) is effective in dealing with the mismatch between thrust and rotor speed in traditional engine control. Among the DTC architecture, model-based thrust estimation method has less arithmetic consumption and better real-time performance. In this paper,a direct thrust controller design approach for gas turbine engine based on parameter dependent model is proposed. In order to ensure the stability of DTC control system based on parameter dependent model, there are usually conservatism detects. For the purpose of reducing the conservatism in the solution process of filter and controller, an Equilibrium Manifold Expansion(EME) model with bounded parameter variation of engine is established. The design conditions of Kalman filter for discrete-time EME system are introduced, and the proposed conditions have a certain suppression effect on the input noise of the system with bounded parameter variation.The engine thrust estimator stability and H∞filtering problems are solved by the polytopic quadratic Lyapunov function based on the Linear Matrix Inequalities(LMIs). To meet the performance requirements of thrust control, the Grey Wolf Optimization(GWO) algorithm is applied to optimize the PID control parameters. The proposed method is verified on a Hardware-in-Loop(HIL) platform. The simulation results demonstrate that the DTC framework can ensure the stability of engine closed-loop system in large range deviation tests. The filter and controller solution method considering the parameter variation boundary can obtain a solution that makes the system have better performance parameters. Moreover, the proposed filter has better thrust estimation performance than the traditional Kalman filter under the condition of sensor noise. Compared with Augmented Linear Quadratic Regulator(ALQR) controller, the PID controller optimized by GWO has a faster response in simulation.
基金supported by Royal Academy of Engineering(IF2223B-125)Royal Society(IECR3213107)。
文摘Laser directed energy deposition(LDED)is an emerging branch of metal-based additive manufacturing(AM)processes,offering unprecedented capabilities for high-performance fabrication with complex geometries and near-net shapes.This technology is gathering increasing attention from industries such as biomedical,automotive,and aerospace.However,achieving consistent part quality and desired material properties is challenging due to intricate processing parameters and potential process defects such as dynamic melt-pool behavior and localized heat accumulation.This paper reviews recent advances in on-line quality control,focusing on in-situ measurement and closed-loop control for efficient assurance of LDED-fabricated parts.The quality principles,encompassing accuracy and material performance,are summarized to lay a foundation for understanding the mechanisms of quality defects and influencing factors.This review explores and thoroughly compares advancements in indirect process measurements,such as optical,thermal,and acoustic monitoring with direct quality measurements,including laser-line scanning and operando synchrotron X-ray imaging.Depending on the sensing techniques,this paper highlights a hierarchical control strategy for adaptive parameter regulation on intra-layer and inter-layer scales.The requirements and performance of various state-of-the-art controllers are critically compared to indicate their suitable applications.The importance of machine learning in detecting process anomalies and predicting build quality based on sensory signals is also outlined.Future directions are proposed towards adaptive,automated,and intelligent quality control,with a focus on multi-modal monitoring,physics-informed neural networks for interpretable analysis,and multi-objective control applications.
基金Aeronautical Science Emphasis foundation of China( 98Z5 2 0 0 1) Delta Power Electronics Science &Education DevelopmentF und
文摘The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.
基金Supported by National Basic Research Program of China(973 Program,Grant No.2011CB711200)National Science and Technology Support Program of China(Grant No.2015BAG17B00)National Natural Science Foundation of China(Grant No.51475333)
文摘For a distributed drive electric vehicle(DDEV)driven by four in-wheel motors,advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently,quickly and precisely.And direct yaw-moment control(DYC)has been widely studied and applied to vehicle stability control.Good vehicle handling performance:quick yaw rate transient response,small overshoot,high steady yaw rate gain,etc,is required by drivers under normal conditions,which is less concerned,however.Based on the hierarchical control methodology,a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed.The upper-loop control system consists of two parts:a state feedback controller,which aims to realize the ideal transient response of yaw rate,with a vehicle sideslip angle observer;and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain.Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors,the integrated time and absolute error(ITAE)function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix.Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method:yaw rate rising time is reduced,steady yaw rate gain is increased,vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced.The control system improves vehicle handling performance under normal conditions in both transient and steady response.State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.
文摘Field trials on a silt-loamy paddy soil derived from shallow-sea deposit in direct seeding rice fields were conducted in Zhejiang, China, in 1996 to compare N efficiency of controlled release fertilizers (LP fertilizers) with the conventional urea. Six treatments including CK (no N fertilizer), conventional urea and different types of LP fertilizers at different rates were designed for two succeeding crops of early and late rice. A blend of different types of LP fertilizers as a single preplant "co-situs" application released N in a rate and amount synchronizing with uptake pattern of direct seeding rice. A single preplant application of the LP fertilizers could meet the N requirement of rice for the whole growth period without need of topdressing. Using LP fertilizer blends, equivalent grain yields could be maintained even if the N fertilization rates were reduced by 25%～50% compared with the conventional urea. Agronomic efficiency of the LP fertilizers was 13.6%～ 86.4% higher than that of the conventional urea in early rice and 100%～164.1% in late rice, depending on the amounts of the LP fertilizers applied. N fertilizer recovery rate increased from 27.4% for the conventional application of urea to 41.7%～54.l% for the single preplant "co-situs" application of the LP fertilizers. Use of the LP fertilizers was promising if the increase in production costs due to the high LP fertilizer prices could be compensated by increase in yield and N efficiency, reduction in labor costs and improvement in environment.
基金supported by National Natural Science Foundation of China(Nos.61603114,61673135)the Fundamental Research Funds for the Central Universities of China(No.HIT.NSRIF.201826)
文摘This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.
文摘Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.
基金the National Natural Science Foundation of China (60374032).
文摘Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.
